Timeapproximation tradeoffs for inapproximable problems
Bonnet, Édouard and Lampis, M and Paschos, V T (2016) Timeapproximation tradeoffs for inapproximable problems. In: 33rd Symposium on Theoretical Aspects of Computer Science, STACS 2016. Leibniz International Proceedings in Informatics, LIPIcs (47). Schloss Dagstuhl LeibnizZentrum für Informatik, Dagstuhl, 22:122:14. ISBN 9783959770019 10.4230/LIPIcs.STACS.2016.22

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Abstract
In this paper we focus on problems which do not admit a constantfactor approximation in polynomial time and explore how quickly their approximability improves as the allowed running time is gradually increased from polynomial to (sub)exponential. We tackle a number of problems: For Min Independent Dominating Set, Max Induced Path, Forest and Tree, for any r(n), a simple, known scheme gives an approximation ratio of r in time roughly rn/r. We show that, for most values of r, if this running time could be significantly improved the ETH would fail. For Max Minimal Vertex Cover we give a nontrivial √rapproximation in time 2n/r. We match this with a similarly tight result. We also give a log rapproximation for Min ATSP in time 2n/r and an rapproximation for Max Grundy Coloring in time rn/r. Furthermore, we show that Min Set Cover exhibits a curious behavior in this superpolynomial setting: for any δ > 0 it admits an mδapproximation, where m is the number of sets, in just quasipolynomial time. We observe that if such ratios could be achieved in polynomial time, the ETH or the Projection Games Conjecture would fail. © Édouard Bonnet, Michael Lampis and Vangelis Th. Paschos; licensed under Creative Commons License CCBY.
Item Type:  Book Section 

Uncontrolled Keywords:  Polynomial approximation; Quasipolynomial time; Minimal vertex cover; Independent dominating set; Constant factor approximation; Approximation ratios; Approximability; Polynomials; Economic and social effects; Computational complexity; Approximation algorithms; Algorithms; REDUCTION; Polynomial and subexponential approximation; Inapproximability; COMPLEXITY; ALGORITHM 
Subjects:  Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány 
Divisions:  Informatics Laboratory 
SWORD Depositor:  MTMT Injector 
Depositing User:  MTMT Injector 
Date Deposited:  08 Feb 2017 13:54 
Last Modified:  21 Jul 2019 14:01 
URI:  https://eprints.sztaki.hu/id/eprint/9071 
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